Knowledge that Transforms

We show that tenth-grade teacher expectations affect students' likelihood of college completion. Our approach leverages a unique feature of a nationally representative dataset: two teachers provided their educational expectations for each student. Identification exploits teacher disagreements about the same student, an idea we formalize using a measurement error model. We estimate an elasticity of college completion with respect to teachers' expectations of 0.12. On average, teachers are overly optimistic, though white teachers are less so with black students. More accurate beliefs are counterproductive if there are returns to optimism or sociodemographic gaps in optimism. We find evidence of both.

This paper develops a theoretical framework to study the critical role that politics play in shaping the spatial dimension of China's urbanization and the related welfare implications. Utilizing a large data set of residential land transactions matched with city leaders in 200 Chinese cities from 2000 through 2011, the empirical analysis finds that a 1 standard deviation increase in the career-incentive measure leads to 9 additional kilometers of outward expansion, a 23% increase relative to the sample average. It also finds some suggestive evidence pointing to the distortionary impacts of overly strong incentives of city leaders on spatial expansion, consistent with the theory.

This paper studies how monetary policy jointly affects asset prices and the real economy in the United States. I develop an estimator that uses high-frequency surprises as a proxy for the structural monetary policy shocks. This is achieved by integrating the surprises into a vector autoregressive model as an exogenous variable. I use current short-term rate surprises because these are least affected by an information effect. When allowing for time-varying model parameters, I find that compared to the response of output, the reaction of stock and house prices to monetary policy shocks was particularly low before the 2007–2009 financial crisis.

This paper proposes a method to estimate unconditional quantile treatment effects (QTEs) given one or more treatment variables, which may be discrete or continuous, even when it is necessary to condition on covariates. The estimator, generalized quantile regression (GQR), is developed in an instrumental variable framework for generality to permit estimation of unconditional QTEs for endogenous policy variables, but it is also applicable in the conditionally exogenous case. The framework includes simultaneous equations models with nonadditive disturbances, which are functions of both unobserved and observed factors. Quantile regression and instrumental variable quantile regression are special cases of GQR and available in this framework.

The Federal Reserve cut interest rates on March 3, 2020, in response to COVID-19. On March 5 and 6, I surveyed over 500 consumers about their concerns about COVID-19, awareness of the Fed's announcement, and macroeconomic expectations. Most consumers were concerned about effects of COVID-19 on the economy, their health, and their personal finances. About 38% were aware that the Fed had cut interest rates. Greater concern is associated with higher inflation expectations and more pessimistic unemployment expectations. I informed respondents about the Fed's announcement, which led some consumers to become more optimistic about unemployment and revise inflation expectations downward.

Using a representative online panel from the United States, we examine how individuals' macroeconomic expectations causally affect their personal economic prospects and their behavior. To exogenously vary respondents' expectations, we provide them with different professional forecasts about the likelihood of a recession. Respondents update their macroeconomic outlook in response to the forecasts, extrapolate to expectations about their personal economic circumstances, and adjust their consumption plans and stock purchases. Extrapolation to expectations about personal unemployment is driven by individuals with higher exposure to macroeconomic risk, consistent with macroeconomic models of imperfect information in which people are inattentive but understand how the economy works.

Job polarization refers to the shrinking share of employment in middle-skill, routine occupations experienced over the past 35 years. Jobless recoveries refers to the slow rebound in aggregate employment following recent recessions despite recoveries in aggregate output. We show how these two phenomena are related. First, essentially all employment loss in routine occupations occurs in economic downturns. Second, jobless recoveries in the aggregate can be accounted for by jobless recoveries in the routine occupations that are disappearing.